To show that our approach applies to a variety of registration tasks, we validate it on three 2D and 3D datasets of different modalities: 4000 T1-weighted Brain-MRI scans [1]}, [2]}, 74 slices of human blood cells of the Platelet-EM dataset [3]}, and 230 time-steps of the cell-tracking video PhC-U373 [4]}, [5]}. All datasets are pre-aligned through affine transformations and split into train, validation, and test sections. We augment each pair of images with random affine transformations during training.
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